The AEO Advantage Index: Why Brands Win or Lose in AI Buyer Journeys — Fireside Chat with Scott Hebner & Brandee Sanders

Julia Nimchinski:
welcome to the show, Scott Hebner and Brandi. senders, two CMOs, one ex-CMO of IBM, and one CMO for more from Salesforce. We just saw the technology before we transition to your session. I’m just curious, do you have any questions for, Alex? Would you use something like that?

Brandee Sanders:
I was gonna say, I have questions, but none will fit the time constraints of the meeting. But thank you for the demo.

Scott Hebner:
Yeah, I just add, you know, I think this kind of automation and giving people dashboards and the ability to manage this and visualize it is really key. It’s a whole new world for everybody, and, you know, people are learning as they go, so… I just caught the last part of it, but it looked very interesting.

Alex Roy:
Yeah, I mean, the key thing I would say is, you know, what we call as controlled autonomy, which is very important. So, you know, the co-pilot, or be it an agent. you know, you need to be able to give it that controlled autonomy as per your organization, goals, so that, you know, that’s, that’s very important, I would say, to configure.
And, you know, you… so that, that way, and especially here, you know, it’s an extension of you, and… As a marketer, and it’s allowing you to do things you always wanted to do. do, but… Never happened.
the resources or the bandwidth, and yeah, so it’s easy, it’s very modular, so it’s easy to kind of, you know, usually most companies start with enabling certain signals, getting the dashboard, you know, looking at it, and then… Going on to enable specific things is how we see, companies roll this out, something like this out.

Julia Nimchinski:
Thank you so much, Alex. What’s the next best step for our audience to just take a test drive here?

Alex Roy:
Yeah, so the best way would be is, you know, just, you can contact me on LinkedIn, and, you know, happy to send you, you know, provision an instance for you, add some credits in it. Happy to have a separate session as well, and, you know, have a deeper dive into it.
You know, the time was limited, we had to kind of breeze over things, and there was a lot of information, but happy to have that one-on-one conversation. My email is alex.roy at salesbox.ai. And, I’m also available on LinkedIn.

Julia Nimchinski:
Thank you so much. And we are transitioning to our next session. We’ll do a proper introduction, Brandi and Scott. And can’t wait to get into the SEO index world. But yeah, how about you actually start with introducing yourself? Friendly.

Brandee Sanders:
For sure. Yeah, so, hi everybody, hello again, HSC Grabs. I’m Brandi Sanders, CMO, Apromoi from Salesforce.
Quite a long track record, don’t want to date myself, but a long track record of working across multiple verticals with, high-growth scrappy startups, as well as with larger enterprise global brands, like, for example, Sony Music, Etsy, Blackline, Salesforce.
I’m super excited as someone who’s both a practitioner as an administrative person working on the deeply technical and operational product engineering side, and then go-to-market, meaning all of those beautiful things that CROs and CMOs are thinking about across generative search and the big change from SEO to AEO and GEO.
So, super excited to MC here with Scott, who actually has a fantastic background as well, so I will hand that microphone over to Scott.

Scott Hebner:
Thank you, Brandy, and it’s good to see you and meet you, and same with you, Julia. We’ve talked a lot, but it’s, good to see some faces here. I am currently the principal analyst for AI at the Cube Research. Which is part of the Silicon Angle media company.
So I’ve been focused on, you know, sort of the next frontiers of AI as sort of a half of my job. The other half is being a CMO practice leader here. And, you know, I’ve spent most of my career being either a product manager or a CMO, and my last role at IBM, before I left there in 2023, was as the CMO for our data and AI business.
So I’ve been deep in the AI space for 10 years, and have quite a bit of marketing and AI, marketing and AI experience to kind of bring all that together. So, excited to be here!

Julia Nimchinski:
Amazing. Brendi, take it away. You’re in mute.

Brandee Sanders:
Go ahead and unmute, Julia. I have not had enough coffee. Don’t worry, hard skills, we’re still here. Alright, so we’re gonna get into it, people.
So, for the last 10 years, if not longer, we know that marketing has billed and been building around one core assumption, and that is that humans and individuals are typically the ones discovering, evaluating, and then also choosing brands, right?
Everything that we do is usually built off of this, but I would say, and Scott, I’m sure you have a lot to say about this, that assumption is definitely breaking.
Because today, if we look at AI, we look at generative, it is increasingly the first, and sometimes, for many deals, depending upon the industry vertical and where you’re operating, it may be the only interaction.
Between you and your buyer, and it’s deciding what is credible, what is relevant, and in many cases, it’s also who even makes that shortlist? Like, who is ranking? What is their weight in Perplexity, in Gemini and ChatGPT?
And so, many companies in 2026, and we see this every day on the CMO and the CRO and the CDO side, is that they’re still measuring success like it is 20… 21.
So they’re looking at traffic, they’re looking at rankings, a blog program, impressions, things that necessarily don’t necessarily tell you, whether or not AI recommends you, and then also it trusts you.
and how it ranks you against your competitors in regards to share of voice.
So, the question I want to open with, and I think, Scott, you’re probably going to have a lot to say about this, so I’m going to mute and let you take the rock, is if… AI is now the primary buyer interface, which, statistically, based off data, we know that it is the majority of the time.
Are most brands still optimizing for an audience that no longer exists? Blog series withstanding.

Scott Hebner:
I think they are, because what’s happening here in the bigger picture is control is shifting from your website and your own channels and your own content into these AI engines, these… essentially creating an AI-mediated buy-in journey. Right? And so the focus on your own domains is only going to get you so far.
So if you’re putting content out there, and you’re doing blogs on your own content, on your own sites, and you’re doing, you know, webinars on your own sites, it’s really important to do that, and to build the mechanics So that AI engines can actually get to that content and understand it.
Right, you know, marketers have built AI websites over the last many years for human beings. to use. Now you have to start to build them for the AI the actual AI engines that, you know, the bots that come by all the time. Some 2% of all website traffic in B2B now is the actual bots.
And they’re checking you out, and they’re trying to figure out what to… Do with your content, and try to understand you, and what you have, and why you matter.
So, yeah, I think you have to start thinking in terms of Control is shifting away, the buyer journey’s being executed in these, you know, AI dialogues, and that’s becoming the buyer journey, certainly in the front end. Right? It’s the shortlisting, it’s the discovery, and that sets the whole context for everything that happens… happens after that.
So, the big question is, how do you influence these engines to mention you, right? To discover you, to cite you, to recommend you, to shortlist you. And that is the big secret that everyone’s trying to figure out right now. And you’re right on the statistics, by the way.
I think G2 just came out with a survey where 26% of B2B buyers started with AI engines last year. Now it’s up to 51%. Our research here at the Cube Research says it’s 56%, so we’ve hit that tipping point. Particularly in B2B, where It’s time to figure this out, because if you fall behind, you may never catch up.

Brandee Sanders:
Yeah, and this is actually… I’ll take it even a step further, because we’re basically… if we’re talking about the internet, we’re talking about systems and models and LLMs that are stack ranking by weighted values, whether that’s… we think it’s more important you have a 5-star review on G2 versus a blog series on whatever it is that you’re specializing in.
But beyond… beyond even that, so, like, is the internet for humans, or is it for agents? Because as we think about this idea, like, the advantages… and you have this in the, in the Advantage Index that I’m, you know, and I’m sure you’ll go into that. We talk about visibility versus diagnosis, and, like.
you know, there’s lots of false positives, I think, that marketers will be looking at in the market, but beyond even the LLMs, agents, Because 18 to 24 months from now, there may be systems involved with all of these different things.
So, like, we’re thinking, we are curating right now for just the LLMs, and understanding, how do I understand my rank and my share of voice and GEO and AEO, and then how do, in your opinion, and then we’ll get into the false positives for sure, and diagnosis, in your opinion, how do you see that changing?
Because it will be agents talking to agents, or agents doing the research, instead of a person just dropping stuff into chat GPT. Like, what do you think that evolution looks like.

Scott Hebner:
Yeah, I think you’re going to be seeing more and more intelligence infused into these buying journeys, where the agents are going to be more autonomous, and they’re going to be able to have more leeway to actually make decisions, right, and explain those decisions, and I think they’re just going to become better at crawling spaces, understanding, and doing it faster.
And when you start to get these agents talking to each other, which is definitely going to start to happen, you start getting this notion of swarm intelligence. And so you’ve got two dynamics that I think, you know, just to start this whole conversation with, that are so different than the world of SEO. You can’t go into AEO with an SEO mentality.
Because with, unlike SEO, which is, you know, you got backlinks, and you got rankings, and you got, you know, you can do paid search, and all that kind of stuff. You can put enough investment in the catch-up if you fall behind. With AEO, what happens is you get a compounding advantage.
Once you establish an advantage, the more the AI engines bring you up, and there’s interaction around you, it strengthens that… that knowledge graph, you know, the vector space. And it grows, and it goes into adjacent spaces, and it’s hard to catch up to that growing Animal, if you will.
And then the other part of it is what you just said, which is, it’s just gonna be hard to… to replicate the kind of content and feed these agents that are going to be more autonomous. So, it’s really important to get started sooner rather than later.

Brandee Sanders:
And it’s interesting, because if AI is deciding who makes the shortlist, and we start integrating with things like agents that operate more autonomously, and might not necessarily be You know, the standard way that we’re thinking about agents right now is, like, is the brand actually being built by those marketers still, or by the machines that are interpreting them, right?

Scott Hebner:
Yeah, and I… it’s… you gotta think of it as it’s not about rankings, it’s about mental models, and these are… you know, the AI engines are becoming more intelligent, and they’re starting to reason, and they’re making conclusions, and… And they’re doing it at unbelievable scale, right?
So it’s about influencing the engines to understand who you are. What you provide, why you matter, to become relevant in the moment of a question, And to validate These engines are going to validate you before they do anything with you, and that means, do they see credibility in your claims?
Do they think you’re authentic, and a practitioner, and have real experience in this? Are you authoritative on the subject? And are you trusted? And that does not come from your own websites. That’s gonna come from the third-party ecosystem, And so… the SEO model’s just not gonna work, because you can’t tell an AI engine what to do.
You have to incent it to learn about you, and to… and that becomes a whole new thing. Definitely.

Brandee Sanders:
What do you mean, the 8-part blog series isn’t going to work? And hey, that is not a mark on content marketing for anyone who is a content marketer. There is a great value in educating your audience base.

Scott Hebner:
Yeah, I would say the anchor is your web… let me just kind of clarify a couple points here that I made, is it’s not that your own channels, your own… your website, your content is not important, it’s perhaps, you know, it’s critical, because… that’s one of the four layers of the model, which maybe we can get into, that these, engines go through.
It’s called Citability Mechanics, and that’s about your content on your website and your channels. are the mechanics there, the technical mechanics, there to be able to get to the content that the AI engine wants to, that you want the AI engine to get to, that’s going to tell about and educate them about you, right?
And it becomes the main source that gets quoted and cited, and you have to have that foundation. Otherwise, you’re only gonna get… you’re only gonna get so far, and part of that is the hygiene of your content.
You know, there’s tricks, like, you gotta structure things differently, you gotta talk more in conversational tones, more questions versus statements. You know, one of the big flaws in this is people make claims. An AI engine will take a claim and try to validate that claim, and if you don’t have validation of the claim.
That’s also in a third party. you know, reinforced by a third party, it’s not going to believe your claim, therefore you’re not credible and trusted, and therefore you’re not going to get recommended.
So there’s a lot of pieces that link together in all this that you need to come together, but it starts with getting your content and your web domain, you know. Built for AI engines, not just human beings.

Brandee Sanders:
Yeah, and I think there’s a lot of technical things there that for most marketers.
who might be coming from a traditional softer approach that aren’t, like, highly as technical, they’re not into data analytics, they… they’re more, like, brand storytelling vision, or softer PMMs who might not be involved with that.
It is a paradigm shift in the way that you view that role as a CMO, and honestly, CDO, CRO. Like, it’s just a huge change in the mindset. Even as recent as the past, like, 6 to 8 months, I think it’s been pretty paramount.

Brandee Sanders:
But I did want to go into something.
So, we talked about advantages with, like, not just visibility, but the diagnosis, and I was pulling this out of, the AAO document that you shared with us.
I would say, so, you argue that the real advantage isn’t visibility, actually, it’s diagnosis, and what would you say, I’m curious, because we’ll do the positive and the negative.
What are the most dangerous false positives that brands are celebrating right now in generative, and the inverse of that that you’re seeing in your experience, Eric?

Scott Hebner:
Yeah, I think the first thing, just to be totally transparent here, there’s no doubt in my mind that we’re somewhere in between an art and a science right now, on really figuring out how these how these AI engines operate, because they are LLMs, they’re statistical animals. And they’re not good at explaining how they derive answers.
So, it is a little bit of an art form, but… and that’s why I think the best way to do this is to interrogate the… interrogate the absolute hell out of the engines to figure out… and they’ll tell you, right? And if you structure things correctly, you can start to figure out why they’re doing things.
And so I think the false positives when you’re doing visibility alone, and what I mean by visibility is dashboards, and instrumentation, and you’re tracking your visibility rate, and your citation rate, and your recommendation rate, and your discovery rate, and And is it positive, is it negative in sentiment?
You can do all that, but if you do it based on keywords, or you make up your own prompt libraries. Then you run into prompt bias, potentially. Right? And… But I think understanding what is happening is very key, so these visibility dashboards and the tools that help you build the hygiene and the mechanics on your content, absolutely critical.
But I think the value Longer term, and how you really create an advantage, is you must understand why those outcomes are happening. Not just what they are, but why are they happening? What are the root causes? And the more you understand what is… how an AI engine actually views you.
And why it is doing certain things, in terms of how it interprets your brand. and what it cites, and all that. That’s the magic, because once you understand why. then you’re able to do the how. That’s Aristotle, right? Cause and effect, right? So that is, I think, the real key.
So, what is good, and I think that’s where we are in the state of things now. Why is the next critical thing that’s diagnostics? And then it’s the diagnostics the root cause, that’s gonna tell you how to really fix things. And that’s what we’ve been trying to anchor on.
But, yeah, there may be false positives, but I think the general direction you get would be correct. And you mentioned, like, content marketers that maybe are storytellers. The AI engines, they determine whether your narrative hangs together.
And one of the fascinating things I’ve found with this is I’ve had one conversation with one big brand, consumer brand, which I can’t name, but they’re blown away by some little competitor they never heard of is ranked right behind them. At number 4. And they’re like, how can that be?
Well, it’s because it’s a new… it’s Greenfield here, because these big companies are gonna suffer from semantic sprawl, because they have so much out there over so many years. Right? And these, you know, semantic clarity is a really big part of all this. So. How does it think about you?
What is… you know, semantically, how do these engines view you? Knowing that is really important to fixing things.

Brandee Sanders:
And… and I want to be mindful of time, because believe it or not, Scott, we’re at the 8-minute mark. So I have one more question, Julia, and then if there’s any Q&A, we will definitely try to leave a fiver.
But this one’s interesting, so… you sit on a board, or you’re with a VC, or you’re running an early-stage startup, or even, honestly, a Goliath enterprise brand, right? And you’re thinking. okay, great, lots of changes are happening.
Say you sit in C-suite, CMO, CRO, CDO, CIO, CTO, regardless of what your title may be, generative will become everyone’s problem, because what I’m thinking is, at what point do these shifts in the market become not just, like, a marketing problem, or a PR problem, or an IT web, because people are going to junk it into technical bales here, but when does it become a revenue risk?
Because I would argue earlier versus later, because it’s a huge part of pipeline and velocity when you really back up into it on how your buyers are finding you is pretty key, especially with intent signals and things like that.
But, like, when… when would the boards, when would the leaders, like, how do you see… what are you seeing on your end?
Like, this is a revenue risk, like, I… Of course, it’s like you roll over and the wrong person does, like, an X post, and all of a sudden, everyone’s talking about generative, but in your opinion, the way that you’re seeing it is, like, when does this become a revenue risk versus just a trend that’s in the market that marketing will kind of come up and zhuzh along with how we’re looking at generative and AI, but rather everyone’s problem, because revenue is everyone’s problem and responsibility in Newark?
Like, how do you see that Shaping in your world right now, from your experiences with your clients?

Scott Hebner:
You know, I’ve been driving the AEO Advantage Index program that we have for almost a year now, and one of the biggest surprises is exactly that. Clearly, it’s a marketing and a communications challenge. Storytelling, demand generation, is all being affected, because the buyer journey is moving there, and you don’t want to become invisible.
Companies are risking becoming invisible to potential buyers. This is a big, big, big deal. But what surprised me was CEOs, for example, are incredibly interested in this, because it’s about brand equity. And some, I think Bloomberg Intelligence, they did a huge study.
Some 40% of institutional investors use these AI engines, these AI assistants, like ChatGPT and Claude and all that, to help do their research on… on companies. And clearly, you know, when they’re doing VCs or funding, and so your brain… it affects brand equity, not just demand generation.
So I think the CEOs are increasingly caring for the investor class Particularly. And then the one that really surprised me was product executives.
If you do the right diagnostics on what these AI engines actually think about you or your competition, what the buyer intent really is, not what you think it is off keywords, but what it really is, it’s a treasure trove of insights to achieve better product-market fit.
Because, after all, these engines are, in many ways, reflecting what everyone’s content is in aggregate, and the questions that are being asked in the dialogues, and it continues to learn. So if you’re a product exec, AEO should really be a big deal to you, too. Right, and obviously the CEO, because of brand equity.
And that’s why this diagnostic, this, you know, it’s a big deal. I mean, there are 19 different Attributes or signals that these engines process when they decide who to surface. And it’s like a linked list. Right? Or a chain. And if any one of those are weak, it can affect the strength of the whole chain.
So, semantic context, topical authority, your credibility, entity relationship. I mean, there’s a whole bunch of these signals that they go through. And you need to know how each one of them you know, score it, if you will. You can actually score them.
1 to 5, and then you start to get the insights of what it thinks about that particular thing, and then you go off and you work on fixing it. So, that’s why I think visibility is only going to get you so far. Tracking metrics. You know, because then you’re guessing, versus having real insights into why.

Brandee Sanders:
Yeah, and it’s just the tip of the iceberg, because the next 6 to 12 months, as with all things in the past year, if there’s any retrospective on 25 and even early 24, is certainly going to be a brand new conversation in the next, like, 6 to 12 months.
We’ll probably be everyone around the roundtable talking about new things that are coming, both from an agentic perspective, and then go-to-market in general for generative and AEO. But Julia, I want to be mindful of time. I know we always come on the clock so much faster than we anticipated.
So where do we stand? Are there any chats from the room, or do we have about 90 seconds for one more zinger?

Julia Nimchinski:
Incredible sessions. Thank you so much, Brandi and Scott. We have a couple of questions here. So, first one, how do you diagnose root cause versus just measuring AO outcomes?

Scott Hebner:
There… you… basically what we have done, we have, like, 120 prompts that represent 60,000 plus words. 380 scoring points, and I think it was 840 formulas, so there’s a research-grade framework. It’s basically a diagnostic and decision framework.
And basically, it reverse engineers how the… how the… how… the observations that the AI engines Have about a brand, or a market category, or a person. and interrogates the world out of it, but then it plays it off each other across the engines.
So you don’t… you do it in ChatGPT, then you play it off the thing in Gemini, then you do it in Grok, and then you do it in Claude, Perplexity, and you start to get a consensus view of things. And… By observing what’s going on, the best way to understand how a brand thinks, or how an engine thinks about you is to interrogate it. Right?
And to reverse engineer its thinking. And that’s basically what this huge library of prompts is designed to do. And it has proven to be successful Because there are certain things… like, I’ll give you one example, just quickly. There was one company I won’t name that was called X. It’s not really X, but it’s… you know, Company X. Well, guess what?
There was another company called X that did something totally different, and the model was confused, because there was entity collision. Right? I mean, you wouldn’t find that out by just measure… by just measurements, or… There was one company that has a really strong story, their mechanics are really good, but they’re never getting recommended.
Well, it turned out that their claims had no proof points. But guess what? They actually did have proof points, but they were in PDFs. So these engines are under token time pressures, and they’ll pass on a PDF every time if there’s a schema Available for the customer proof points.
So they actually had it, but it, you know, just because you have it doesn’t mean the AI engine recognizes it and is visible to it, or decides to take the energy and time to try to understand it. So you start to learn all these little things. like that, right?
And whether your narrative hangs together, and why it doesn’t hang together, and do you have enough third-party reinforcement in the right areas To become trustworthy and author… viewed as being authoritative, and it’s that linked list of those 19 things, and who best to tell you than coming from the mouth of the, What’s the saying, you know?
From the mouth of the whatever, right from them, right from the mouth of the AI engines.

Julia Nimchinski:
That’s awesome. Scott, what’s your… just advice for anyone who would like to just get started with this. Should they reach out to you directly, or… How should they learn more?

Scott Hebner:
Yeah, I would say, two things. One, specifically, feel free to reach out to me on LinkedIn, Scott Hebner, you can find me there, or through you guys, through the, Hard Skill Exchange. Or you can go to thecuberesearch.com, and you can, you can find me there. I’ll be glad to talk with everybody. I have two kinds… I have a different kind of research.
I have research just on how these AI engines work and operate. That has nothing to do with how you diagnose it, that’s… right? But it all… so my second piece of advice for everyone is spend some time Digging into how these AI engines actually determine who to surface.
interrogate the hell out of the AI engines and start to learn how they think, you know, how they reason. Because understanding all that is the key, and if you come out to, you know, the websites I just mentioned, or come to me, I’ll get you some starting point places to go to understand this.
you know, whether you want to do diagnostic work or not, it’s good to understand, you know, these 19 signals that I referred to. They’re the core signals.
Don’t just depend on the top-level metrics, and don’t make assumptions on how things work, because I’m finding that every assumption I had across a lot of things didn’t really turn out to be the right assumption. It’s a learning, and that’s why I said, you know, we talked before about it is somewhere between an art and a science right now.
No one has the perfect answers, but The best proxy right now, I think, is, you know, some of the approaches that I’ve been outlining.

Julia Nimchinski:
Thank you so much again, and Randy, before we wrap this up, tell us, what’s the latest and greatest with you? What’s your AEO strategy?

Brandee Sanders:
Oh, well, I’m usually in degenerative and understanding shared voice, so, like, I feel like Scott and I are kindred spirits.
I don’t have anything as quite as polished as the AEO Advantage, but I spend a great deal of time working with people to kind of understand If I go to search for you, and Scott made a great point about naming conventions, because I just had this happen with a friend of mine who was renaming a product, entered into GPT, they had already named the product, and then it came up, and there was something that was not, like, not safe for work.
that came up with that exact same name in the GPT and in Gemini and Perplexity.
And so I think, like, being aware of this as a pre-thing, not like an afterthought, but rather having generative and AEO at the front of what you’re doing, and influencing what you’re doing, both from a product perspective and understanding the landscape, and then secondly, from go-to-market, whether you’re a CMO, CDOC, or RO, you really should be thinking, in the same way you’d be thinking about your rocks, your OKRs, or your KPIs for the board deck.
Generative should have its own slot in there, not as an afterthought, but rather as something that’s proactive, so… Very much so.
We’ll be talking about this… we’ll be talking about it at Salesforce World Tour, in New York and Toronto and Washington, D.C, so come out and see us, and we’ll talk about it.

Scott Hebner:
It’s making marketing cool again. I mean, it’s gonna affect the entire business. Great.

Julia Nimchinski:
This is awesome. Thank you so much. Thank you. And that’s a wrap for our days free of the Agentech OS Summit. Incredibly grateful for all of you watching, all of our speakers, all of the VCs and operators, and AI Native founders, and analysts. And yeah, we’re gonna return on May 7th with our next AI practice sessions.
So, super practical sessions and showcases of the most innovative GTM methods and micro-methodologies, and don’t forget that you can book the majority of our speakers for a one-on-one session On our coaching marketplace. And yeah… See you soon. Thank you so much.

Brandee Sanders:
Thanks, everyone.